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Record W7161936119 · doi:10.82308/34350

Examining Adult Oral Interaction Within an ESL Classroom: influences of gender and culture

2023· dissertation· en· W7161936119 on OpenAlexaboutno aff
Victoria Goodhand

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsLikert scaleEnglish as a second languageFocus groupSecond languageScale (ratio)Language proficiencyAdult educationFirst language

Abstract

fetched live from OpenAlex

This study examines the influence of student gender and culture on oral participation in English as a Second Language (ESL) classes. Seven adult students who had recently immigrated to Canada participated in the study. I examined the experiences of students in their adult education course. Gender was the primary focus of the research, and the influence of culture was also a secondary point of consideration. The study integrated a mixed-methods approach to data collection, using a Likert scale survey, classroom observations, and semi-structured interviews. The results of the study displayed gender differences related to topics of discussion, frequency of participation, rate of interruption, and the home cultures of the students. By identifying gender-rooted imbalances, educators can actively implement educational structures that discourage gender-based inequalities in the ESL classroom. The findings of the study could, in turn, impact: the selected classroom activities, group pairings, and topics of discussion. Keywords: ESL education, second language acquisition, educational inequalities, gender

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.104
GPT teacher head0.327
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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